Call For Papers

With the increasing amount of traffic information collected through automatic number plate reading systems (NPRS), it is highly desirable for police activities and investigations to find meaningful traffic patterns from the accumulated massive historical dataset in order to identify potential criminal behaviors. Nowadays, NPRS sensors are widely spread on Italian highways making the collection of traffic data more accessible to Italian police, Polizia di Stato.

However, analyzing traffic data in order to find potential criminal behaviors is challenging due to the huge size of the dataset and the complexity and dynamics of traffic phenomena.

The focus of this conference is to develop and employ automatic traffic analysis systems that can detect, track and in general understand the behavior of road-users in order to identify criminal behaviors. For example, most of the criminal activities on Italian highways are perpetrated by criminal drivers in rest stop or service areas. Those drivers often exhibit a recurring highway-dart-in-and-out behavior aimed at moving from one service area to another in order to find a suitable target as part of their victim selection process.

The scientist, or research group (RG), is totally free to present contributions with or without the use of the datasets that are provided below.
In case of studies carried out with our datasets, the scientist (or RG) is again totally free to try to satisfy the shared-task goal, or to face any other open research problem.

This conference aims to gather not only data mining researchers interested in these topics, but also traffic researchers and decision makers. Original research papers related to the following topics, as well as papers regarding other topics that could be relevant in this area, are welcome:
detection and tracking of road users (vehicles, bikes, trucks, etc.);
behavior understanding of road users;
automatic understanding of the environment in traffic scenarios;
applications related to traffic surveillance;
vehicle accident analysis.

Aiming at focusing the efforts on a common goal, a dataset is provided. It contains transits recorded using several gates. Records are referred to the transits of a limited area of Italy, in which gates are homogeneously distributed. The plates are coherently anonymized (a plate is always referred using the same ID). The dataset can be downloaded filling a little form about the affiliation, and other preliminary non-binding indications.

With the intent to unify the way experimental results are evaluated and to push research forwards the development of a real working system supporting police activity, a shared task is proposed.

The main practical goal is to identify itineraries that could imply a criminal intent. The scientist (or RG) is free to define the concept of itinerary, formalizing it functionally to the proposing approach. Other open data can be integrated in the itinerary features or not, up to the scientist (or RG). Criminal intents could be described, for instance, as follows:

the sequential visit of service areas each facing the other;
the sequential visit of service areas in the same direction;
transits inconsistent under the space-time point of view, that are the proof of cloned plates;
combinations of the previous cases involving several plates and possibly the same criminal organization;
and so on.
There are no restrictions about methods or techniques. There are only two requirements to participate in this shared task, that are:

the use of a virtual machine (VM) to send us the system, such a strategy will make it easier to validate each participant's results;
the representation formalism of the output (details can be found below), in this way our systems will be able to build an overall report about results, in order to better evaluate the final outcome.